Statistical Evaluation of Bioequivalence Studies - BEBAC ...

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Studiesof >2 formulations• Disadvantages• Not mentioned in any guideline – exceptBrazil’s ANVISA.• Statistical analysis more complicated –especially in the case of drop outs.• May need measures against multiplicity,increasing the sample size.Dissolution Testing, Bioavailability & Bioequivalence | Budapest, 24 May 2007 29
Page 1: Statistical Evaluation ofBioequival
Page 7: Assumptions: StatisticsMultiplicati
Page 12: Nonparametrics5. In which cases may
Page 16 and 17: Acceptance range for C max2. Assess
Page 18 and 19: Outliers• Problems• Parametric
Page 20 and 21: Outliers• Solution II• Stay wit
Page 22 and 23: Re-testing of subjectsn=24: 83.3%-1
Page 24 and 25: Add-on Design• Reasonable,• if
Page 26 and 27: Group Sequential Design± EU• Per
Page 30 and 31: Studiesof >2 formulations• Bonfer
Page 32 and 33: Parallel Groups• Sometimes it is
Page 35 and 36: Sample data set• Will be used thr
Page 37 and 38: Parallel Groups: Example• Evaluat
Page 39 and 40: Side noteValidated?Sure!But what if
Page 41 and 42: Sample Size• Maximum Number of Su
Page 43 and 44: Sample Size: Planning• NfG on the
Page 49 and 50: Sample Size: PowerPower to show BEw
Page 51: Sample Size: PowerEffect of drop-ou
Page 57 and 58: Sample Size: Sensitivity Analysis
Page 62 and 63: Nuisance: period effectTreatment ef
Page 64 and 65: Nuisance: sequence effect• ‘Two
Page 66 and 67: Nuisance: sequence effect• These
Page 68 and 69: Are we making progress?PubMed/MedLi
Page 70 and 71: Bell curve (and beyond?)• Abraham
Page 72 and 73: Conclusions, Outlook• David Bourn
Page 74: Important Documents• EMEA• Bios

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